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Found 22 papers, 7 papers with code
Wavelet-Based Dual-Branch Network for Image Demoiréing
When smartphone cameras are used to take photos of digital screens, usually moire patterns result, severely degrading photo quality.
Graph Neural Networks in Vision-Language Image Understanding: A Survey
2D image understanding is a complex problem within Computer Vision, but it holds the key to providing human level scene comprehension.
Low-Light Video Enhancement with Synthetic Event Guidance
Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving.
Disentangling 3D Attributes from a Single 2D Image: Human Pose, Shape and Garment
Specifically, we focus on human appearance and learn implicit pose, shape and garment representations of dressed humans from RGB images.
SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes
To further leverage these two paradigms, we propose a selective and joint HDR and denoising (SJ-HD$^2$R) imaging framework, utilizing scenario-specific priors to conduct the path selection with an accuracy of more than 93. 3$\%$.
TAPE: Task-Agnostic Prior Embedding for Image Restoration
In this paper, we propose a novel approach that embeds a task-agnostic prior into a transformer.
SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers
For zero-shot image restoration, we design a novel model, termed SiamTrans, which is constructed by Siamese transformers, encoders, and decoders.
Wavelet-Based Network For High Dynamic Range Imaging
The frequency-guided upsampling module reconstructs details from multiple frequency-specific components with rich details.
Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs
In this paper, we propose a self-adaptive learning method for demoiréing a high-frequency image, with the help of an additional defocused moiré-free blur image.
Self-Adaptively Learning to Demoire from Focused and Defocused Image Pairs
In this paper, we propose a self-adaptive learning method for demoireing a high-frequency image, with the help of an additional defocused moire-free blur image.
Video Super-resolution with Temporal Group Attention
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention.
Wavelet-Based Dual-Branch Network for Image Demoireing
When smartphone cameras are used to take photos of digital screens, usually moire patterns result, severely degrading photo quality.
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
Image Demoireing with Learnable Bandpass Filters
Image demoireing is a multi-faceted image restoration task involving both texture and color restoration.
Ranked #2 on
Image Enhancement
on TIP 2018
(using extra training data)
AIM 2019 Challenge on Image Demoireing: Methods and Results
A new dataset, called LCDMoire was created for this challenge, and consists of 10, 200 synthetically generated image pairs (moire and clean ground truth).
AIM 2019 Challenge on Image Demoireing: Dataset and Study
In addition to describing the dataset and its creation, this paper also reviews the challenge tracks, competition, and results, the latter summarizing the current state-of-the-art on this dataset.
RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images
We explore different ways of using this privileged information: (1) using depth data to initially train a depth-based network, (2) using the features from the depth-based network of the paired depth images to constrain mid-level RGB network weights, and (3) using the foreground mask, obtained from the depth data, to suppress the responses from the background area.
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
Ranked #4 on
Hand Pose Estimation
on HANDS 2017
The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation
We present the 2017 Hands in the Million Challenge, a public competition designed for the evaluation of the task of 3D hand pose estimation.
BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysis
We also show significant improvements in egocentric hand pose estimation with a CNN trained on the new dataset.
First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations
Our dataset and experiments can be of interest to communities of 3D hand pose estimation, 6D object pose, and robotics as well as action recognition.
Spatial Attention Deep Net with Partial PSO for Hierarchical Hybrid Hand Pose Estimation
In this paper, a hybrid hand pose estimation method is proposed by applying the kinematic hierarchy strategy to the input space (as well as the output space) of the discriminative method by a spatial attention mechanism and to the optimization of the generative method by hierarchical Particle Swarm Optimization (PSO).
